Use this url to cite publication: https://hdl.handle.net/20.500.12259/54408
Application of the biologically inspired network for electroencephalogram analysis
Type of publication
Straipsnis Web of Science ir Scopus duomenų bazėje / Article in Web of Science and Scopus database (S1)
Author(s)
Author | Affiliation | |
---|---|---|
LT | ||
Kauno technologijos universitetas | LT |
Title [en]
Application of the biologically inspired network for electroencephalogram analysis
Is part of
Computational intelligence : theory and applications international conference, 7th Fuzzy Days Dortmund, Germany, October 1–3, 2001 : proceedings. Berlin, Heidelberg : Springer, 2001
Date Issued
Date |
---|
2001 |
Publisher
Berlin, Heidelberg : Springer, 2001
Publisher (trusted)
Extent
p. 18-27
Abstract (en)
Architecture of a neural network combining automatic feature extraction with the minimized amount of network training acquired by means of employing of a multistage training procedure is investigated. The network selects prototypical signals and calculates features based on the similarity of a signal to prototypes. The similarity is measured by the prognosis error of the linear regression model. The network is applied for the meaningful paroxysmal activity vs. background classification task and provides better accuracy than the methods using manually selected features. Performance of several modifications of the new architecture is being evaluated.
Series/Report no.
(Lecture Notes in Computer Science. Vol. 2206 0302-9743)
Type of document
type::text::journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Vokietija / Germany (DE)
ISBN (of the container)
9783540427322
ISSN (of the container)
0302-9743
WOS
WOS:000237080600004
Other Identifier(s)
VDU02-000008329
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
LECTURE NOTES IN COMPUTER SCIENCE | 0.415 | 0 | 0 | 0 | 1 | 0 | 2001 | Q3 |
Journal | IF | AIF | AIF (min) | AIF (max) | Cat | AV | Year | Quartile |
---|---|---|---|---|---|---|---|---|
LECTURE NOTES IN COMPUTER SCIENCE | 0.415 | 0 | 0 | 0 | 1 | 0 | 2001 | Q3 |